{
 "cells": [
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "# 泰坦尼克号 - 灾难中的机器学习（进阶版）\n",
    "\n",
    "![](./../img/1.png)"
   ],
   "id": "6c533f56b053e049"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "**目标：**\n",
    "\n",
    "根据所给出的泰坦尼克号乘客的信息，预测乘客在此次事件中是否生还。"
   ],
   "id": "b4a69a9cc94ce0be"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:13.086427Z",
     "start_time": "2025-04-09T10:40:12.105944Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ],
   "id": "a3fcb730e5897172",
   "outputs": [],
   "execution_count": 1
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "## 一、数据集",
   "id": "4e69c3e38e6d3ea8"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "### 数据标签\n",
    "\n",
    "|     特征      |    定义     |                                   其他                                    | 类型  |\n",
    "|:-----------:|:---------:|:-----------------------------------------------------------------------:|:---:|\n",
    "| PassengerId |    ID     |                                    \\                                    | 连续型 |\n",
    "|  Survived   |   是否幸存    |                            \t0 = No, 1 = Yes                             | 离散型 |\n",
    "|   Pclass    |    票类     |           \t1 = 1st (Upper), 2 = 2nd (Middle), 3 = 3rd (Lower)           | 离散型 |\n",
    "|    Name     |    姓名     |                                    \\                                    |  \\  |\n",
    "|     Sex     |    性别     |                           male 男性, female 女性                            | 离散型 |\n",
    "|     Age     |    年龄     |                              如果年龄小于1，则为小数                               | 连续型 |\n",
    "|    SibSp    | 兄弟姐妹/配偶人数 |          兄弟姐妹 = 兄弟 + 姐妹 + 继兄弟 + 继姐妹<br/>配偶 = 丈夫 + 妻子（情妇和未婚夫除外）          | 离散型 |\n",
    "|    Parch    |   父母/孩子   | 父母 = 母亲 + 父亲<br/>孩子 = 女儿 + 儿子 + 继女 + 继子<br/>有些孩子只和保姆一起旅行，因此对他们来说parch=0 | 离散型 |\n",
    "|   Ticket    |   船票号码    |                                用于区分不同的乘客                                | 连续型 |\n",
    "|    Fare     |    票价     |                                   英镑                                    | 连续型 |\n",
    "|    Cabin    |    舱室     |                                乘客所住的船舱编号                                |  \\  |\n",
    "|  Embarked   |   登船港口    |             C = Cherbourg, Q = Queenstown, S = Southampton              | 离散型 |"
   ],
   "id": "3aa854aedf53fafa"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "### 导入数据",
   "id": "ba2268026c7dbe27"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:15.111792Z",
     "start_time": "2025-04-09T10:40:15.085367Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# 取出训练数据，并分为特征集与目标集\n",
    "df_train = pd.read_csv('./../data/train.csv')\n",
    "y_train = df_train['Survived']\n",
    "del df_train['Survived']\n",
    "# 取出测试数据\n",
    "df_test = pd.read_csv('./../data/test.csv')\n",
    "# 合并为组合数据\n",
    "df = pd.concat([df_train, df_test], axis=0).reset_index()\n",
    "del df['index']"
   ],
   "id": "373c0ce13ef0d0cd",
   "outputs": [],
   "execution_count": 2
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:15.376622Z",
     "start_time": "2025-04-09T10:40:15.370740Z"
    }
   },
   "cell_type": "code",
   "source": "df_train.shape",
   "id": "c09ee5566ba01ffc",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(891, 11)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 3
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:15.771300Z",
     "start_time": "2025-04-09T10:40:15.766597Z"
    }
   },
   "cell_type": "code",
   "source": "df.shape",
   "id": "4411107e154e6789",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1309, 11)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 4
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:16.432620Z",
     "start_time": "2025-04-09T10:40:16.423116Z"
    }
   },
   "cell_type": "code",
   "source": "df.head()",
   "id": "8ac711bbdc15098a",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "   PassengerId  Pclass                                               Name  \\\n",
       "0            1       3                            Braund, Mr. Owen Harris   \n",
       "1            2       1  Cumings, Mrs. John Bradley (Florence Briggs Th...   \n",
       "2            3       3                             Heikkinen, Miss. Laina   \n",
       "3            4       1       Futrelle, Mrs. Jacques Heath (Lily May Peel)   \n",
       "4            5       3                           Allen, Mr. William Henry   \n",
       "\n",
       "      Sex   Age  SibSp  Parch            Ticket     Fare Cabin Embarked  \n",
       "0    male  22.0      1      0         A/5 21171   7.2500   NaN        S  \n",
       "1  female  38.0      1      0          PC 17599  71.2833   C85        C  \n",
       "2  female  26.0      0      0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3  female  35.0      1      0            113803  53.1000  C123        S  \n",
       "4    male  35.0      0      0            373450   8.0500   NaN        S  "
      ],
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 5
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "## 二、数据预处理",
   "id": "36712f33eabf8e3a"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:17.454326Z",
     "start_time": "2025-04-09T10:40:17.447666Z"
    }
   },
   "cell_type": "code",
   "source": "df.isna().sum(axis=0)",
   "id": "af18b1abd54977e8",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PassengerId       0\n",
       "Pclass            0\n",
       "Name              0\n",
       "Sex               0\n",
       "Age             263\n",
       "SibSp             0\n",
       "Parch             0\n",
       "Ticket            0\n",
       "Fare              1\n",
       "Cabin          1014\n",
       "Embarked          2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 6
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "***PassengerID***\n",
    "\n",
    "无效数据"
   ],
   "id": "5bc369978c6adc59"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "***Pclass***\n",
    "\n",
    "阶级缩影\n",
    "\n",
    "One-Hot 编码"
   ],
   "id": "3cb24776429a7c14"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:18.650261Z",
     "start_time": "2025-04-09T10:40:18.645828Z"
    }
   },
   "cell_type": "code",
   "source": "X = pd.get_dummies(df['Pclass'], prefix='Pclass').astype(int)",
   "id": "966cb6dea3e140fa",
   "outputs": [],
   "execution_count": 7
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "***Name***\n",
    "\n",
    "称呼的隐含信息"
   ],
   "id": "456847bec07044d1"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:19.256966Z",
     "start_time": "2025-04-09T10:40:19.252959Z"
    }
   },
   "cell_type": "code",
   "source": "Call = df['Name'].map(lambda x: x.split(',')[1].split('.')[0].strip())",
   "id": "e2094190c2e65106",
   "outputs": [],
   "execution_count": 8
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "One-Hot 编码",
   "id": "34541e4921a70991"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:19.696035Z",
     "start_time": "2025-04-09T10:40:19.690803Z"
    }
   },
   "cell_type": "code",
   "source": "X = pd.concat([X, pd.get_dummies(Call, prefix='Call').astype(int)], axis=1)",
   "id": "bab5ee3ba75fa949",
   "outputs": [],
   "execution_count": 9
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "***Sex***\n",
    "\n",
    "性别对生存的影响"
   ],
   "id": "67b2ce579f2d77e9"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:20.081314Z",
     "start_time": "2025-04-09T10:40:20.076885Z"
    }
   },
   "cell_type": "code",
   "source": "X['Sex'] = (df['Sex'] == 'male').astype(int)",
   "id": "d6e98d57bfe1ddbb",
   "outputs": [],
   "execution_count": 10
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "***Age***\n",
    "\n",
    "年龄对生存的影响"
   ],
   "id": "c643d680622f2140"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "如何填充缺失值？\n",
    "\n",
    "- 用 平均数 | 中位数 | 众数 ？共缺失 263 条数据，数据量较多，不够精准；\n",
    "- 用 Pclass | Embarked 分组聚合取平均？其本身类别较少；\n",
    "- 用 SibSp | Parch 分组聚合取平均？没有可解释性；\n",
    "- **用 Call 分组聚合取平均？类别多且每个类别也间接代表了年龄。**"
   ],
   "id": "abbb6da2952a4b11"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:20.587464Z",
     "start_time": "2025-04-09T10:40:20.577132Z"
    }
   },
   "cell_type": "code",
   "source": [
    "md = pd.concat([Call, df['Age']], axis=1)\n",
    "call_age = md.groupby('Name').agg({'Age': 'mean'}).round(1)\n",
    "call_age.to_csv('./../data/call_age.csv')\n",
    "call_age"
   ],
   "id": "d1518fa8f0a1707d",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "               Age\n",
       "Name              \n",
       "Capt          70.0\n",
       "Col           54.0\n",
       "Don           40.0\n",
       "Dona          39.0\n",
       "Dr            43.6\n",
       "Jonkheer      38.0\n",
       "Lady          48.0\n",
       "Major         48.5\n",
       "Master         5.5\n",
       "Miss          21.8\n",
       "Mlle          24.0\n",
       "Mme           24.0\n",
       "Mr            32.3\n",
       "Mrs           37.0\n",
       "Ms            28.0\n",
       "Rev           41.2\n",
       "Sir           49.0\n",
       "the Countess  33.0"
      ],
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Capt</th>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Col</th>\n",
       "      <td>54.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Don</th>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dona</th>\n",
       "      <td>39.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dr</th>\n",
       "      <td>43.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jonkheer</th>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lady</th>\n",
       "      <td>48.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Major</th>\n",
       "      <td>48.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Master</th>\n",
       "      <td>5.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miss</th>\n",
       "      <td>21.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mlle</th>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mme</th>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mr</th>\n",
       "      <td>32.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mrs</th>\n",
       "      <td>37.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ms</th>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rev</th>\n",
       "      <td>41.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sir</th>\n",
       "      <td>49.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>the Countess</th>\n",
       "      <td>33.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 11
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:20.846373Z",
     "start_time": "2025-04-09T10:40:20.835734Z"
    }
   },
   "cell_type": "code",
   "source": [
    "X_age = np.empty((md.shape[0], 1))\n",
    "# itertuples() 此函数的索引有问题\n",
    "for i, call, age in md.itertuples():\n",
    "    if pd.isna(age):\n",
    "        X_age[i] = call_age.loc[call]\n",
    "    else:\n",
    "        X_age[i] = age\n",
    "X['Age'] = X_age"
   ],
   "id": "fa9c97ca8fc035f3",
   "outputs": [],
   "execution_count": 12
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "***各个称呼所代表的含义***\n",
    "\n",
    "---\n",
    "\n",
    "|         称谓         |            含义             |\n",
    "|:------------------:|:-------------------------:|\n",
    "|   Capt（Captain）    |      船长、上尉（海军或陆军军衔）       |\n",
    "|    Col（Colonel）    |         上校（高级军官）          |\n",
    "|        Don         |    西班牙语中对男性的尊称（类似“先生”）    |\n",
    "|        Dona        | 西班牙语中对女性的尊称（类似“女士”或“夫人”）  |\n",
    "|     Dr（Doctor）     |           博士或医生           |\n",
    "|      Jonkheer      |   荷兰低阶贵族头衔，意为“阁下”或“少爷”    |\n",
    "|        Lady        | 英国女性贵族头衔（如伯爵夫人），或对女性的礼貌称呼 |\n",
    "|       Major        |         少校（中级军官）          |\n",
    "|       Master       |        旧时对未成年男孩的称呼        |\n",
    "|        Miss        |           未婚女性            |\n",
    "| Mlle（Mademoiselle） |      法语中的“小姐”（未婚女性）       |\n",
    "|    Mme（Madame）     |     法语中的“夫人”（已婚或年长女性）     |\n",
    "|     Mr（Mister）     |         成年男性的通用称呼         |\n",
    "|    Mrs（Missus）     |        已婚女性，传统上随夫姓        |\n",
    "|         Ms         |    女性通用称呼，婚姻状况不明或不愿透露     |\n",
    "|   Rev（Reverend）    |          牧师或神职人员          |\n",
    "|        Sir         |         对骑士或男爵的尊称         |\n",
    "|    the Countess    |         女伯爵或伯爵夫人          |"
   ],
   "id": "5fcefc2de890e475"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "***SibSp | Parch***\n",
    "\n",
    "同辈和长晚辈对生存的影响"
   ],
   "id": "60daa184c24b3e27"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:21.759861Z",
     "start_time": "2025-04-09T10:40:21.755205Z"
    }
   },
   "cell_type": "code",
   "source": "X[['SibSp', 'Parch']] = df[['SibSp', 'Parch']]",
   "id": "c7b1d48f50c8d84b",
   "outputs": [],
   "execution_count": 13
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "***组合 Family***",
   "id": "e20b464616c6c8e2"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:22.260659Z",
     "start_time": "2025-04-09T10:40:22.256209Z"
    }
   },
   "cell_type": "code",
   "source": "X['Family'] = df['SibSp'] + df['Parch'] + 1",
   "id": "c8d9820ba177ad90",
   "outputs": [],
   "execution_count": 14
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "***Ticket***\n",
    "\n",
    "票号区间所代表的隐藏含义"
   ],
   "id": "f9f57b25be924f5f"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:22.598520Z",
     "start_time": "2025-04-09T10:40:22.594438Z"
    }
   },
   "cell_type": "code",
   "source": "X['Ticket'] = df['Ticket'].map(lambda x: x.split(' ')[-1] if x != 'LINE' else 70000)",
   "id": "65498abd44a3c0e2",
   "outputs": [],
   "execution_count": 15
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "***Fare***\n",
    "\n",
    "反映家庭经济情况"
   ],
   "id": "176e93e65ce59f71"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:22.904133Z",
     "start_time": "2025-04-09T10:40:22.897423Z"
    }
   },
   "cell_type": "code",
   "source": "df[df['Fare'].isna()]",
   "id": "e0b130135a48469c",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "      PassengerId  Pclass                Name   Sex   Age  SibSp  Parch  \\\n",
       "1043         1044       3  Storey, Mr. Thomas  male  60.5      0      0   \n",
       "\n",
       "     Ticket  Fare Cabin Embarked  \n",
       "1043   3701   NaN   NaN        S  "
      ],
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       "      <td>Storey, Mr. Thomas</td>\n",
       "      <td>male</td>\n",
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       "      <td>0</td>\n",
       "      <td>3701</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 16
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "60多岁的一个老头孤身一人，按照三等票的平均票费填充",
   "id": "42b2a973331ae8e3"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:23.237439Z",
     "start_time": "2025-04-09T10:40:23.232240Z"
    }
   },
   "cell_type": "code",
   "source": [
    "fill_fare = df.groupby('Pclass')['Fare'].mean().round(4).loc[3]\n",
    "X['Fare'] = df['Fare'].fillna(fill_fare)\n",
    "fill_fare"
   ],
   "id": "ccdf15601be5c0b0",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(13.3029)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 17
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "***家庭单人票价 Single_Fare***",
   "id": "19c466b0067d91e7"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:24.112272Z",
     "start_time": "2025-04-09T10:40:24.108586Z"
    }
   },
   "cell_type": "code",
   "source": "X['Single_Fare'] = (X['Fare'] / X['Family']).round(4)",
   "id": "d47d0854d1a55bb5",
   "outputs": [],
   "execution_count": 18
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "***Cabin***\n",
    "\n",
    "船舱号反映生存位置"
   ],
   "id": "47eeb505353368fa"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:24.737108Z",
     "start_time": "2025-04-09T10:40:24.732968Z"
    }
   },
   "cell_type": "code",
   "source": "1014 / df.shape[0]",
   "id": "5c2eb85ce4538686",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.774637127578304"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 19
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "**缺失 77% 的数据，且无法通过其他数据印证补充**",
   "id": "1328e3d5daa7921b"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "***Embarked***\n",
    "\n",
    "登船地点潜藏阶级"
   ],
   "id": "a0699c75aae4db5d"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:25.864054Z",
     "start_time": "2025-04-09T10:40:25.856970Z"
    }
   },
   "cell_type": "code",
   "source": "df[df['Embarked'].isna()]",
   "id": "707d00abfced6d3a",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "     PassengerId  Pclass                                       Name     Sex  \\\n",
       "61            62       1                        Icard, Miss. Amelie  female   \n",
       "829          830       1  Stone, Mrs. George Nelson (Martha Evelyn)  female   \n",
       "\n",
       "      Age  SibSp  Parch  Ticket  Fare Cabin Embarked  \n",
       "61   38.0      0      0  113572  80.0   B28      NaN  \n",
       "829  62.0      0      0  113572  80.0   B28      NaN  "
      ],
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       "      <th>61</th>\n",
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       "      <td>Icard, Miss. Amelie</td>\n",
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       "      <td>80.0</td>\n",
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       "      <td>80.0</td>\n",
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       "      <td>NaN</td>\n",
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       "</table>\n",
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     },
     "execution_count": 20,
     "metadata": {},
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   ],
   "execution_count": 20
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "根据她们的姓氏推测：（AI网络搜索）\n",
    "\n",
    "- Icard, Miss. Amelie ：法国雇佣女仆\n",
    "- Stone, Mrs. George Nelson (Martha Evelyn) ：美国社交名流\n",
    "\n",
    "二人乘坐泰坦尼克号返回美国，大概率是从 **法国瑟堡(C)** 登船（泰坦尼克号在瑟堡接载了 274 名乘客，多为头等舱）"
   ],
   "id": "20ce64c3123e3cc9"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "One-Hot 编码",
   "id": "4274d13c5b536735"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:26.704180Z",
     "start_time": "2025-04-09T10:40:26.699910Z"
    }
   },
   "cell_type": "code",
   "source": "X = pd.concat([X, pd.get_dummies(df['Embarked'].fillna('C'), prefix='Embarked').astype(int)], axis=1)",
   "id": "c6e61ba8415e8c30",
   "outputs": [],
   "execution_count": 21
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "### 处理后的数据",
   "id": "cd4196c141e2bc2f"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:27.088452Z",
     "start_time": "2025-04-09T10:40:27.078475Z"
    }
   },
   "cell_type": "code",
   "source": "X.head()",
   "id": "afac1e063ce8f61c",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "   Pclass_1  Pclass_2  Pclass_3  Call_Capt  Call_Col  Call_Don  Call_Dona  \\\n",
       "0         0         0         1          0         0         0          0   \n",
       "1         1         0         0          0         0         0          0   \n",
       "2         0         0         1          0         0         0          0   \n",
       "3         1         0         0          0         0         0          0   \n",
       "4         0         0         1          0         0         0          0   \n",
       "\n",
       "   Call_Dr  Call_Jonkheer  Call_Lady  ...   Age  SibSp  Parch  Family  \\\n",
       "0        0              0          0  ...  22.0      1      0       2   \n",
       "1        0              0          0  ...  38.0      1      0       2   \n",
       "2        0              0          0  ...  26.0      0      0       1   \n",
       "3        0              0          0  ...  35.0      1      0       2   \n",
       "4        0              0          0  ...  35.0      0      0       1   \n",
       "\n",
       "    Ticket     Fare  Single_Fare  Embarked_C  Embarked_Q  Embarked_S  \n",
       "0    21171   7.2500       3.6250           0           0           1  \n",
       "1    17599  71.2833      35.6416           1           0           0  \n",
       "2  3101282   7.9250       7.9250           0           0           1  \n",
       "3   113803  53.1000      26.5500           0           0           1  \n",
       "4   373450   8.0500       8.0500           0           0           1  \n",
       "\n",
       "[5 rows x 32 columns]"
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 32 columns</p>\n",
       "</div>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 22
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:28.067235Z",
     "start_time": "2025-04-09T10:40:28.063283Z"
    }
   },
   "cell_type": "code",
   "source": [
    "X_train = X.iloc[:df_train.shape[0]]\n",
    "X_test = X.iloc[df_train.shape[0]:]"
   ],
   "id": "165356eb466d2747",
   "outputs": [],
   "execution_count": 23
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "## 三、模型选择与评估\n",
    "\n",
    "- 逻辑回归 --> LogisticRegression\n",
    "- 决策树 --> DecisionTreeClassifier\n",
    "- 随机森林 --> RandomForestClassifier\n",
    "- AdaBoost --> AdaBoostClassifier\n",
    "- GBDT --> GradientBoostingClassifier\n",
    "- 堆叠 --> StackingClassifier\n",
    "- 软投票与硬投票 --> VotingClassifier\n",
    "\n",
    "（目前我学过的）"
   ],
   "id": "885adb5c09c0ee87"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "***想法：***\n",
    "\n",
    "先使用决策树将参数调制最优，再过渡到 随机森林 | AdaBoost | GBDT 中，最后尝试 投票 和 堆叠。\n",
    "\n",
    "（尝试的每一个模型最后都会进行预测并提交答案）"
   ],
   "id": "7fd33eacb3dfd3bd"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "### 决策树",
   "id": "eabfc990e615a478"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "#### 特征选择与参数选择\n",
    "\n",
    "卡方检验、max_depth、min_samples_leaf"
   ],
   "id": "e6c5a3a5717598ab"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:32.582392Z",
     "start_time": "2025-04-09T10:40:31.115950Z"
    }
   },
   "cell_type": "code",
   "source": [
    "from sklearn.feature_selection import SelectKBest, chi2\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.model_selection import cross_val_score"
   ],
   "id": "5b2d62da75215979",
   "outputs": [],
   "execution_count": 24
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "调节参数时 random_state 不设置",
   "id": "84140e401be0d67d"
  },
  {
   "metadata": {},
   "cell_type": "code",
   "source": [
    "best_mean_score = 0\n",
    "best_combo = ()\n",
    "for k in range(2, X.shape[1]):\n",
    "    for depth in range(2, 20):\n",
    "        for sample in range(1, 20):\n",
    "            \n",
    "            selector = SelectKBest(chi2, k=k)\n",
    "            X_new = selector.fit_transform(X_train, y_train)\n",
    "            \n",
    "            dt_clf = DecisionTreeClassifier(max_depth=depth, min_samples_leaf=sample)\n",
    "            scores = cross_val_score(dt_clf, X_new, y_train, cv=5, scoring='accuracy')\n",
    "            mean_score = np.mean(scores)\n",
    "            \n",
    "            if mean_score > best_mean_score:\n",
    "                best_mean_score = mean_score\n",
    "                best_combo = (k, depth, sample)\n",
    "            \n",
    "    print(best_combo)\n",
    "\n",
    "print(best_mean_score, best_combo)"
   ],
   "id": "dbf2ca6536587dad",
   "outputs": [],
   "execution_count": null
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "**当 k=10, depth=7, sample=12 时准确率最高**",
   "id": "f5bf333cd3b19b64"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:34.474565Z",
     "start_time": "2025-04-09T10:40:34.462400Z"
    }
   },
   "cell_type": "code",
   "source": [
    "best_selector = SelectKBest(chi2, k=10)\n",
    "X_train_new = best_selector.fit_transform(X_train, y_train)\n",
    "X_test_new = best_selector.transform(X_test)\n",
    "X_train_new"
   ],
   "id": "b55ec08ba7fc4422",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0, 1, 0, ..., '21171', 7.25, 3.625],\n",
       "       [1, 0, 0, ..., '17599', 71.2833, 35.6416],\n",
       "       [0, 1, 1, ..., '3101282', 7.925, 7.925],\n",
       "       ...,\n",
       "       [0, 1, 1, ..., '6607', 23.45, 5.8625],\n",
       "       [1, 0, 0, ..., '111369', 30.0, 30.0],\n",
       "       [0, 1, 0, ..., '370376', 7.75, 7.75]], dtype=object)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 25
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "Call_Mrs | Pclass_3 | Call_Miss | Sex | Pclass_1 | Call_Mr | Age | Ticket | Fare | Single_Fare",
   "id": "a6aaaaf2aa74652e"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:36.847344Z",
     "start_time": "2025-04-09T10:40:36.836304Z"
    }
   },
   "cell_type": "code",
   "source": [
    "beat_dt_clf = DecisionTreeClassifier(max_depth=7, min_samples_leaf=12, random_state=42)\n",
    "beat_dt_clf.fit(X_train_new, y_train)\n",
    "beat_dt_clf.score(X_train_new, y_train)"
   ],
   "id": "beb25e7733497298",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8630751964085297"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 26
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:40:38.999340Z",
     "start_time": "2025-04-09T10:40:38.994446Z"
    }
   },
   "cell_type": "code",
   "source": "beat_dt_clf.feature_importances_",
   "id": "4f2dcd56ef6dab3a",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.        , 0.12076021, 0.        , 0.5199436 , 0.        ,\n",
       "       0.03919957, 0.06726406, 0.08842847, 0.08236524, 0.08203885])"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 27
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T10:47:33.722499Z",
     "start_time": "2025-04-09T10:47:29.920099Z"
    }
   },
   "cell_type": "code",
   "source": [
    "from sklearn.tree import plot_tree\n",
    "plt.figure(figsize=(40, 20))\n",
    "plot_tree(beat_dt_clf, class_names=['0', '1'], filled=True, rounded=True)\n",
    "plt.savefig('./../img/result1_1.png', dpi=300, bbox_inches='tight')\n",
    "plt.show()"
   ],
   "id": "1a71634b0d7a0a45",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 4000x2000 with 1 Axes>"
      ],
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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 36
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-05T10:20:58.893556Z",
     "start_time": "2025-04-05T10:20:58.887147Z"
    }
   },
   "cell_type": "code",
   "source": [
    "Survived = pd.DataFrame(beat_dt_clf.predict(X_test_new), columns=['Survived'])\n",
    "result = pd.concat([df_test['PassengerId'], Survived], axis=1)\n",
    "result.to_csv('./../data/result1.csv', index=False)"
   ],
   "id": "a1f93df6e3d4e26c",
   "outputs": [],
   "execution_count": 34
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "![](./../img/result1.png)\n",
    "\n",
    "分数仅仅提升了 1%，排名直接提升了 7000 多名！"
   ],
   "id": "97b4734e3b7e9bbf"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-07T00:46:27.142366Z",
     "start_time": "2025-04-07T00:46:27.137952Z"
    }
   },
   "cell_type": "code",
   "source": "328 / 418",
   "id": "ff85ff0c47cd4a3f",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.784688995215311"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 29
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "### 随机森林",
   "id": "23f9c5557c2542a7"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T01:57:33.723043Z",
     "start_time": "2025-04-09T01:57:33.674539Z"
    }
   },
   "cell_type": "code",
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "# 网格搜索\n",
    "from sklearn.model_selection import GridSearchCV"
   ],
   "id": "5c3baee0f1c90519",
   "outputs": [],
   "execution_count": 28
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-06T02:33:59.925213Z",
     "start_time": "2025-04-06T01:43:59.544862Z"
    }
   },
   "cell_type": "code",
   "source": [
    "param_grid = {\n",
    "    'n_estimators': range(50, 200, 5), \n",
    "    'max_depth': range(2, 10), \n",
    "    'min_samples_leaf': range(1, 15)\n",
    "}\n",
    "grid = GridSearchCV(RandomForestClassifier(oob_score=True, n_jobs=-1), param_grid, cv=5, n_jobs=-1)\n",
    "grid.fit(X_train_new, y_train)\n",
    "grid.best_params_"
   ],
   "id": "a41a0525a390238b",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'max_depth': 8, 'min_samples_leaf': 2, 'n_estimators': 55}"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 49
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "{'max_depth': 8, 'min_samples_leaf': 2, 'n_estimators': 55}",
   "id": "2721a072e1243762"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T02:42:44.020788Z",
     "start_time": "2025-04-09T02:42:43.929551Z"
    }
   },
   "cell_type": "code",
   "source": [
    "beat_rf_clf = RandomForestClassifier(n_estimators=55, max_depth=8, min_samples_leaf=2, oob_score=True, n_jobs=-1, random_state=42)\n",
    "beat_rf_clf.fit(X_train_new, y_train)\n",
    "beat_rf_clf.oob_score_"
   ],
   "id": "6690c5c75ec32825",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8417508417508418"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 87
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T01:57:37.064561Z",
     "start_time": "2025-04-09T01:57:37.040065Z"
    }
   },
   "cell_type": "code",
   "source": "beat_rf_clf.score(X_train_new, y_train)",
   "id": "28b0827ef01276c1",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9169472502805837"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 30
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-06T08:22:44.925274Z",
     "start_time": "2025-04-06T08:22:44.898089Z"
    }
   },
   "cell_type": "code",
   "source": [
    "Survived = pd.DataFrame(beat_rf_clf.predict(X_test_new), columns=['Survived'])\n",
    "result = pd.concat([df_test['PassengerId'], Survived], axis=1)\n",
    "result.to_csv('./../data/result2.csv', index=False)"
   ],
   "id": "2b0211cd8d935cba",
   "outputs": [],
   "execution_count": 97
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "![](./../img/result2.png)",
   "id": "86119d2cc409cf8a"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-07T00:46:55.516594Z",
     "start_time": "2025-04-07T00:46:55.512100Z"
    }
   },
   "cell_type": "code",
   "source": "331 / 418",
   "id": "3c9ead3344aaeb9f",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7918660287081339"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 34
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "***再次提升，多作对了3个！***\n",
    "\n",
    "- 尝试过直接使用 X_train ，利用随机森林进行特征选择，但事实证明这只会导致过拟合，32个特征值中弱相关性数据过多。\n",
    "- 只使用 n_estimators 大概率会过拟合"
   ],
   "id": "7d5b167455a0ffc9"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "### 逻辑回归",
   "id": "b9d5236ead7599d8"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T01:57:41.857839Z",
     "start_time": "2025-04-09T01:57:41.853070Z"
    }
   },
   "cell_type": "code",
   "source": "from sklearn.linear_model import LogisticRegression",
   "id": "2a8c0edb6200adc3",
   "outputs": [],
   "execution_count": 31
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T02:02:51.020444Z",
     "start_time": "2025-04-09T02:02:43.793292Z"
    }
   },
   "cell_type": "code",
   "source": [
    "score_list = []\n",
    "for i in range(200, 600, 10):\n",
    "    lr_clf = LogisticRegression(max_iter=i, n_jobs=-1, warm_start=True)\n",
    "    scores = cross_val_score(lr_clf, X_train_new, y_train, cv=5, scoring='accuracy')\n",
    "    score_list.append(np.mean(scores))\n",
    "plt.plot(range(200, 600, 10), score_list, 'g-')"
   ],
   "id": "7f2486c2c76a2970",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x21cfeecf090>]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 59
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T02:02:52.624239Z",
     "start_time": "2025-04-09T02:02:52.620714Z"
    }
   },
   "cell_type": "code",
   "source": "max(score_list)",
   "id": "fe05893c238c5e69",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(0.800207143305505)"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 60
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T02:01:07.831230Z",
     "start_time": "2025-04-09T02:01:07.793319Z"
    }
   },
   "cell_type": "code",
   "source": [
    "best_lr_clf = LogisticRegression(max_iter=500, n_jobs=-1, random_state=42)\n",
    "best_lr_clf.fit(X_train_new, y_train)\n",
    "best_lr_clf.score(X_train_new, y_train)"
   ],
   "id": "4e7af3b97ed3836e",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8013468013468014"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 48
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-08T09:57:56.757717Z",
     "start_time": "2025-04-08T09:57:56.751439Z"
    }
   },
   "cell_type": "code",
   "source": [
    "Survived = pd.DataFrame(best_lr_clf.predict(X_test_new), columns=['Survived'])\n",
    "result = pd.concat([df_test['PassengerId'], Survived], axis=1)\n",
    "result.to_csv('./../data/result.csv', index=False)"
   ],
   "id": "3ceb7eb6d4e82d8",
   "outputs": [],
   "execution_count": 207
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "0.78299",
   "id": "bf33314461d2f641"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "### AdaBoost",
   "id": "84b66cd4c546a9e1"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T01:58:02.065033Z",
     "start_time": "2025-04-09T01:58:02.062513Z"
    }
   },
   "cell_type": "code",
   "source": "from sklearn.ensemble import AdaBoostClassifier",
   "id": "688f8de293fb567",
   "outputs": [],
   "execution_count": 33
  },
  {
   "metadata": {},
   "cell_type": "code",
   "source": [
    "for depth in range(3, 10):\n",
    "    best_score = 0\n",
    "    best_param = dict()\n",
    "    for sample in range(2, 15):\n",
    "        ada_clf = AdaBoostClassifier(DecisionTreeClassifier(max_depth=depth, min_samples_leaf=sample))\n",
    "        param_grid = {'n_estimators': range(1, 101)}\n",
    "        grid = GridSearchCV(ada_clf, param_grid, cv=5, n_jobs=-1)\n",
    "        grid.fit(X_train_new, y_train)\n",
    "        \n",
    "        if best_score < grid.best_score_:\n",
    "            best_score = grid.best_score_\n",
    "            best_param = grid.best_params_ | {'max_depth': depth, 'min_samples_leaf': sample}\n",
    "    print(best_score, best_param)"
   ],
   "id": "21cbdecf34fda7aa",
   "outputs": [],
   "execution_count": null
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T01:58:10.787958Z",
     "start_time": "2025-04-09T01:58:09.322430Z"
    }
   },
   "cell_type": "code",
   "source": [
    "ada_clf = AdaBoostClassifier(\n",
    "    DecisionTreeClassifier(max_depth=3, min_samples_leaf=13), \n",
    "    n_estimators=90, random_state=42\n",
    ")\n",
    "scores = cross_val_score(ada_clf, X_train_new, y_train, cv=5, scoring='accuracy')\n",
    "np.mean(scores)"
   ],
   "id": "c480b03e8007647d",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(0.8350511581193898)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 34
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T01:58:12.830019Z",
     "start_time": "2025-04-09T01:58:12.575115Z"
    }
   },
   "cell_type": "code",
   "source": [
    "ada_clf.fit(X_train_new, y_train)\n",
    "ada_clf.score(X_train_new, y_train)"
   ],
   "id": "63d885ae96366647",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9169472502805837"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 35
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-08T09:54:32.513586Z",
     "start_time": "2025-04-08T09:54:32.482508Z"
    }
   },
   "cell_type": "code",
   "source": [
    "Survived = pd.DataFrame(ada_clf.predict(X_test_new), columns=['Survived'])\n",
    "result = pd.concat([df_test['PassengerId'], Survived], axis=1)\n",
    "result.to_csv('./../data/result3.csv', index=False)"
   ],
   "id": "645695d9f6dbd811",
   "outputs": [],
   "execution_count": 196
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "0.77511",
   "id": "5c3280c5c273237a"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "### GBDT",
   "id": "1aa6a7eaff856625"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T01:58:18.364071Z",
     "start_time": "2025-04-09T01:58:18.360566Z"
    }
   },
   "cell_type": "code",
   "source": "from sklearn.ensemble import GradientBoostingClassifier",
   "id": "5de8ef39b508e6c4",
   "outputs": [],
   "execution_count": 36
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-07T03:19:03.490323Z",
     "start_time": "2025-04-07T03:09:52.731365Z"
    }
   },
   "cell_type": "code",
   "source": [
    "param_grid = {\n",
    "    'n_estimators': range(100, 300, 10), \n",
    "    'max_depth': range(3, 10), \n",
    "    'min_samples_leaf': range(1, 15)\n",
    "}\n",
    "grid = GridSearchCV(GradientBoostingClassifier(warm_start=True), param_grid, cv=5, n_jobs=-1)\n",
    "grid.fit(X_train_new, y_train)\n",
    "grid.best_params_"
   ],
   "id": "c40b809c3496e042",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'max_depth': 4, 'min_samples_leaf': 5, 'n_estimators': 110}"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 89
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T01:58:24.227382Z",
     "start_time": "2025-04-09T01:58:22.933439Z"
    }
   },
   "cell_type": "code",
   "source": [
    "gbdt_clf = GradientBoostingClassifier(n_estimators=110, max_depth=4, min_samples_leaf=5, random_state=42)\n",
    "scores = cross_val_score(gbdt_clf, X_train_new, y_train, cv=5, scoring='accuracy')\n",
    "np.mean(scores)"
   ],
   "id": "da6d3b898a1fea94",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(0.8485091959073504)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 37
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T01:58:25.403861Z",
     "start_time": "2025-04-09T01:58:25.218184Z"
    }
   },
   "cell_type": "code",
   "source": [
    "gbdt_clf.fit(X_train_new, y_train)\n",
    "gbdt_clf.score(X_train_new, y_train)"
   ],
   "id": "c94ce43e311a8c97",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9393939393939394"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 38
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-07T07:28:05.836521Z",
     "start_time": "2025-04-07T07:28:05.825175Z"
    }
   },
   "cell_type": "code",
   "source": [
    "Survived = pd.DataFrame(gbdt_clf.predict(X_test_new), columns=['Survived'])\n",
    "result = pd.concat([df_test['PassengerId'], Survived], axis=1)\n",
    "result.to_csv('./../data/result4.csv', index=False)"
   ],
   "id": "ceb5e81b20dd6333",
   "outputs": [],
   "execution_count": 37
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "0.77511",
   "id": "e1d5b4e4f1b0ae3a"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "### 投票\n",
    "\n",
    "不加入逻辑回归"
   ],
   "id": "a409df0891a82f5d"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T01:59:51.128343Z",
     "start_time": "2025-04-09T01:59:51.125308Z"
    }
   },
   "cell_type": "code",
   "source": "from sklearn.ensemble import VotingClassifier",
   "id": "981f19bd71fed792",
   "outputs": [],
   "execution_count": 41
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T01:59:51.680137Z",
     "start_time": "2025-04-09T01:59:51.675690Z"
    }
   },
   "cell_type": "code",
   "source": [
    "estimators = [\n",
    "    ('DecisionTree', DecisionTreeClassifier(max_depth=7, min_samples_leaf=12, random_state=42)),\n",
    "    ('RandomForest', RandomForestClassifier(n_estimators=55, max_depth=8, min_samples_leaf=2, n_jobs=-1, random_state=42)),\n",
    "    ('AdaBoost', AdaBoostClassifier(DecisionTreeClassifier(max_depth=3, min_samples_leaf=13), n_estimators=90, random_state=42)), \n",
    "    ('GradientBoosting', GradientBoostingClassifier(n_estimators=110, max_depth=4, min_samples_leaf=5, random_state=42))\n",
    "]"
   ],
   "id": "3c6597f0b7a6d31e",
   "outputs": [],
   "execution_count": 42
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T01:59:52.392066Z",
     "start_time": "2025-04-09T01:59:52.377345Z"
    }
   },
   "cell_type": "code",
   "source": [
    "vote_hard_clf = VotingClassifier(estimators=estimators, voting='hard', n_jobs=-1)\n",
    "vote_hard_clf"
   ],
   "id": "29caea85f054aad0",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "VotingClassifier(estimators=[('DecisionTree',\n",
       "                              DecisionTreeClassifier(max_depth=7,\n",
       "                                                     min_samples_leaf=12,\n",
       "                                                     random_state=42)),\n",
       "                             ('RandomForest',\n",
       "                              RandomForestClassifier(max_depth=8,\n",
       "                                                     min_samples_leaf=2,\n",
       "                                                     n_estimators=55, n_jobs=-1,\n",
       "                                                     random_state=42)),\n",
       "                             ('AdaBoost',\n",
       "                              AdaBoostClassifier(estimator=DecisionTreeClassifier(max_depth=3,\n",
       "                                                                                  min_samples_leaf=13),\n",
       "                                                 n_estimators=90,\n",
       "                                                 random_state=42)),\n",
       "                             ('GradientBoosting',\n",
       "                              GradientBoostingClassifier(max_depth=4,\n",
       "                                                         min_samples_leaf=5,\n",
       "                                                         n_estimators=110,\n",
       "                                                         random_state=42))],\n",
       "                 n_jobs=-1)"
      ],
      "text/html": [
       "<style>#sk-container-id-1 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: #000;\n",
       "  --sklearn-color-text-muted: #666;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-1 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-1 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: flex;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "  align-items: start;\n",
       "  justify-content: space-between;\n",
       "  gap: 0.5em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label .caption {\n",
       "  font-size: 0.6rem;\n",
       "  font-weight: lighter;\n",
       "  color: var(--sklearn-color-text-muted);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-1 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-1 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 0.5em;\n",
       "  text-align: center;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>VotingClassifier(estimators=[(&#x27;DecisionTree&#x27;,\n",
       "                              DecisionTreeClassifier(max_depth=7,\n",
       "                                                     min_samples_leaf=12,\n",
       "                                                     random_state=42)),\n",
       "                             (&#x27;RandomForest&#x27;,\n",
       "                              RandomForestClassifier(max_depth=8,\n",
       "                                                     min_samples_leaf=2,\n",
       "                                                     n_estimators=55, n_jobs=-1,\n",
       "                                                     random_state=42)),\n",
       "                             (&#x27;AdaBoost&#x27;,\n",
       "                              AdaBoostClassifier(estimator=DecisionTreeClassifier(max_depth=3,\n",
       "                                                                                  min_samples_leaf=13),\n",
       "                                                 n_estimators=90,\n",
       "                                                 random_state=42)),\n",
       "                             (&#x27;GradientBoosting&#x27;,\n",
       "                              GradientBoostingClassifier(max_depth=4,\n",
       "                                                         min_samples_leaf=5,\n",
       "                                                         n_estimators=110,\n",
       "                                                         random_state=42))],\n",
       "                 n_jobs=-1)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" ><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label  sk-toggleable__label-arrow\"><div><div>VotingClassifier</div></div><div><a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.ensemble.VotingClassifier.html\">?<span>Documentation for VotingClassifier</span></a><span class=\"sk-estimator-doc-link \">i<span>Not fitted</span></span></div></label><div class=\"sk-toggleable__content \"><pre>VotingClassifier(estimators=[(&#x27;DecisionTree&#x27;,\n",
       "                              DecisionTreeClassifier(max_depth=7,\n",
       "                                                     min_samples_leaf=12,\n",
       "                                                     random_state=42)),\n",
       "                             (&#x27;RandomForest&#x27;,\n",
       "                              RandomForestClassifier(max_depth=8,\n",
       "                                                     min_samples_leaf=2,\n",
       "                                                     n_estimators=55, n_jobs=-1,\n",
       "                                                     random_state=42)),\n",
       "                             (&#x27;AdaBoost&#x27;,\n",
       "                              AdaBoostClassifier(estimator=DecisionTreeClassifier(max_depth=3,\n",
       "                                                                                  min_samples_leaf=13),\n",
       "                                                 n_estimators=90,\n",
       "                                                 random_state=42)),\n",
       "                             (&#x27;GradientBoosting&#x27;,\n",
       "                              GradientBoostingClassifier(max_depth=4,\n",
       "                                                         min_samples_leaf=5,\n",
       "                                                         n_estimators=110,\n",
       "                                                         random_state=42))],\n",
       "                 n_jobs=-1)</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><label>DecisionTree</label></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" ><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label  sk-toggleable__label-arrow\"><div><div>DecisionTreeClassifier</div></div><div><a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.tree.DecisionTreeClassifier.html\">?<span>Documentation for DecisionTreeClassifier</span></a></div></label><div class=\"sk-toggleable__content \"><pre>DecisionTreeClassifier(max_depth=7, min_samples_leaf=12, random_state=42)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><label>RandomForest</label></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label  sk-toggleable__label-arrow\"><div><div>RandomForestClassifier</div></div><div><a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.ensemble.RandomForestClassifier.html\">?<span>Documentation for RandomForestClassifier</span></a></div></label><div class=\"sk-toggleable__content \"><pre>RandomForestClassifier(max_depth=8, min_samples_leaf=2, n_estimators=55,\n",
       "                       n_jobs=-1, random_state=42)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><label>AdaBoost</label></div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" ><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label  sk-toggleable__label-arrow\"><div><div>estimator: DecisionTreeClassifier</div></div></label><div class=\"sk-toggleable__content \"><pre>DecisionTreeClassifier(max_depth=3, min_samples_leaf=13)</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" ><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label  sk-toggleable__label-arrow\"><div><div>DecisionTreeClassifier</div></div><div><a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.tree.DecisionTreeClassifier.html\">?<span>Documentation for DecisionTreeClassifier</span></a></div></label><div class=\"sk-toggleable__content \"><pre>DecisionTreeClassifier(max_depth=3, min_samples_leaf=13)</pre></div> </div></div></div></div></div></div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><label>GradientBoosting</label></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-6\" type=\"checkbox\" ><label for=\"sk-estimator-id-6\" class=\"sk-toggleable__label  sk-toggleable__label-arrow\"><div><div>GradientBoostingClassifier</div></div><div><a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.ensemble.GradientBoostingClassifier.html\">?<span>Documentation for GradientBoostingClassifier</span></a></div></label><div class=\"sk-toggleable__content \"><pre>GradientBoostingClassifier(max_depth=4, min_samples_leaf=5, n_estimators=110,\n",
       "                           random_state=42)</pre></div> </div></div></div></div></div></div></div></div></div>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 43
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T01:59:53.256490Z",
     "start_time": "2025-04-09T01:59:53.237431Z"
    }
   },
   "cell_type": "code",
   "source": [
    "vote_soft_clf = VotingClassifier(estimators=estimators, voting='soft', n_jobs=-1)\n",
    "vote_soft_clf"
   ],
   "id": "8e4382d99194153a",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "VotingClassifier(estimators=[('DecisionTree',\n",
       "                              DecisionTreeClassifier(max_depth=7,\n",
       "                                                     min_samples_leaf=12,\n",
       "                                                     random_state=42)),\n",
       "                             ('RandomForest',\n",
       "                              RandomForestClassifier(max_depth=8,\n",
       "                                                     min_samples_leaf=2,\n",
       "                                                     n_estimators=55, n_jobs=-1,\n",
       "                                                     random_state=42)),\n",
       "                             ('AdaBoost',\n",
       "                              AdaBoostClassifier(estimator=DecisionTreeClassifier(max_depth=3,\n",
       "                                                                                  min_samples_leaf=13),\n",
       "                                                 n_estimators=90,\n",
       "                                                 random_state=42)),\n",
       "                             ('GradientBoosting',\n",
       "                              GradientBoostingClassifier(max_depth=4,\n",
       "                                                         min_samples_leaf=5,\n",
       "                                                         n_estimators=110,\n",
       "                                                         random_state=42))],\n",
       "                 n_jobs=-1, voting='soft')"
      ],
      "text/html": [
       "<style>#sk-container-id-2 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: #000;\n",
       "  --sklearn-color-text-muted: #666;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-2 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-2 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: flex;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "  align-items: start;\n",
       "  justify-content: space-between;\n",
       "  gap: 0.5em;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label .caption {\n",
       "  font-size: 0.6rem;\n",
       "  font-weight: lighter;\n",
       "  color: var(--sklearn-color-text-muted);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-2 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-2 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-2 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-2 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 0.5em;\n",
       "  text-align: center;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-2 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>VotingClassifier(estimators=[(&#x27;DecisionTree&#x27;,\n",
       "                              DecisionTreeClassifier(max_depth=7,\n",
       "                                                     min_samples_leaf=12,\n",
       "                                                     random_state=42)),\n",
       "                             (&#x27;RandomForest&#x27;,\n",
       "                              RandomForestClassifier(max_depth=8,\n",
       "                                                     min_samples_leaf=2,\n",
       "                                                     n_estimators=55, n_jobs=-1,\n",
       "                                                     random_state=42)),\n",
       "                             (&#x27;AdaBoost&#x27;,\n",
       "                              AdaBoostClassifier(estimator=DecisionTreeClassifier(max_depth=3,\n",
       "                                                                                  min_samples_leaf=13),\n",
       "                                                 n_estimators=90,\n",
       "                                                 random_state=42)),\n",
       "                             (&#x27;GradientBoosting&#x27;,\n",
       "                              GradientBoostingClassifier(max_depth=4,\n",
       "                                                         min_samples_leaf=5,\n",
       "                                                         n_estimators=110,\n",
       "                                                         random_state=42))],\n",
       "                 n_jobs=-1, voting=&#x27;soft&#x27;)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-7\" type=\"checkbox\" ><label for=\"sk-estimator-id-7\" class=\"sk-toggleable__label  sk-toggleable__label-arrow\"><div><div>VotingClassifier</div></div><div><a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.ensemble.VotingClassifier.html\">?<span>Documentation for VotingClassifier</span></a><span class=\"sk-estimator-doc-link \">i<span>Not fitted</span></span></div></label><div class=\"sk-toggleable__content \"><pre>VotingClassifier(estimators=[(&#x27;DecisionTree&#x27;,\n",
       "                              DecisionTreeClassifier(max_depth=7,\n",
       "                                                     min_samples_leaf=12,\n",
       "                                                     random_state=42)),\n",
       "                             (&#x27;RandomForest&#x27;,\n",
       "                              RandomForestClassifier(max_depth=8,\n",
       "                                                     min_samples_leaf=2,\n",
       "                                                     n_estimators=55, n_jobs=-1,\n",
       "                                                     random_state=42)),\n",
       "                             (&#x27;AdaBoost&#x27;,\n",
       "                              AdaBoostClassifier(estimator=DecisionTreeClassifier(max_depth=3,\n",
       "                                                                                  min_samples_leaf=13),\n",
       "                                                 n_estimators=90,\n",
       "                                                 random_state=42)),\n",
       "                             (&#x27;GradientBoosting&#x27;,\n",
       "                              GradientBoostingClassifier(max_depth=4,\n",
       "                                                         min_samples_leaf=5,\n",
       "                                                         n_estimators=110,\n",
       "                                                         random_state=42))],\n",
       "                 n_jobs=-1, voting=&#x27;soft&#x27;)</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><label>DecisionTree</label></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-8\" type=\"checkbox\" ><label for=\"sk-estimator-id-8\" class=\"sk-toggleable__label  sk-toggleable__label-arrow\"><div><div>DecisionTreeClassifier</div></div><div><a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.tree.DecisionTreeClassifier.html\">?<span>Documentation for DecisionTreeClassifier</span></a></div></label><div class=\"sk-toggleable__content \"><pre>DecisionTreeClassifier(max_depth=7, min_samples_leaf=12, random_state=42)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><label>RandomForest</label></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-9\" type=\"checkbox\" ><label for=\"sk-estimator-id-9\" class=\"sk-toggleable__label  sk-toggleable__label-arrow\"><div><div>RandomForestClassifier</div></div><div><a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.ensemble.RandomForestClassifier.html\">?<span>Documentation for RandomForestClassifier</span></a></div></label><div class=\"sk-toggleable__content \"><pre>RandomForestClassifier(max_depth=8, min_samples_leaf=2, n_estimators=55,\n",
       "                       n_jobs=-1, random_state=42)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><label>AdaBoost</label></div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-10\" type=\"checkbox\" ><label for=\"sk-estimator-id-10\" class=\"sk-toggleable__label  sk-toggleable__label-arrow\"><div><div>estimator: DecisionTreeClassifier</div></div></label><div class=\"sk-toggleable__content \"><pre>DecisionTreeClassifier(max_depth=3, min_samples_leaf=13)</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-11\" type=\"checkbox\" ><label for=\"sk-estimator-id-11\" class=\"sk-toggleable__label  sk-toggleable__label-arrow\"><div><div>DecisionTreeClassifier</div></div><div><a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.tree.DecisionTreeClassifier.html\">?<span>Documentation for DecisionTreeClassifier</span></a></div></label><div class=\"sk-toggleable__content \"><pre>DecisionTreeClassifier(max_depth=3, min_samples_leaf=13)</pre></div> </div></div></div></div></div></div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><label>GradientBoosting</label></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-12\" type=\"checkbox\" ><label for=\"sk-estimator-id-12\" class=\"sk-toggleable__label  sk-toggleable__label-arrow\"><div><div>GradientBoostingClassifier</div></div><div><a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.ensemble.GradientBoostingClassifier.html\">?<span>Documentation for GradientBoostingClassifier</span></a></div></label><div class=\"sk-toggleable__content \"><pre>GradientBoostingClassifier(max_depth=4, min_samples_leaf=5, n_estimators=110,\n",
       "                           random_state=42)</pre></div> </div></div></div></div></div></div></div></div></div>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 44
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T02:01:21.353123Z",
     "start_time": "2025-04-09T02:01:15.467902Z"
    }
   },
   "cell_type": "code",
   "source": [
    "for model in (best_lr_clf, beat_dt_clf, beat_rf_clf, ada_clf, gbdt_clf, vote_hard_clf, vote_soft_clf):\n",
    "    scores = cross_val_score(model, X_train_new, y_train, cv=5, scoring='accuracy')\n",
    "    print(model.__class__.__name__, ':', np.mean(scores))"
   ],
   "id": "afe325175beaea0b",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LogisticRegression : 0.800207143305505\n",
      "DecisionTreeClassifier : 0.8361559224154165\n",
      "RandomForestClassifier : 0.8305442219571904\n",
      "AdaBoostClassifier : 0.8350511581193898\n",
      "GradientBoostingClassifier : 0.8485091959073504\n",
      "VotingClassifier : 0.8485029188374866\n",
      "VotingClassifier : 0.8473730462620048\n"
     ]
    }
   ],
   "execution_count": 49
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T02:01:25.690867Z",
     "start_time": "2025-04-09T02:01:25.343728Z"
    }
   },
   "cell_type": "code",
   "source": [
    "vote_hard_clf.fit(X_train_new, y_train)\n",
    "vote_hard_clf.score(X_train_new, y_train)"
   ],
   "id": "cd885924b919afb2",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.920314253647587"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 50
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T02:01:27.122047Z",
     "start_time": "2025-04-09T02:01:26.813142Z"
    }
   },
   "cell_type": "code",
   "source": [
    "vote_soft_clf.fit(X_train_new, y_train)\n",
    "vote_soft_clf.score(X_train_new, y_train)"
   ],
   "id": "f65359650f647f23",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9090909090909091"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 51
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T02:02:26.733338Z",
     "start_time": "2025-04-09T02:02:26.667449Z"
    }
   },
   "cell_type": "code",
   "source": [
    "Survived = pd.DataFrame(vote_hard_clf.predict(X_test_new), columns=['Survived'])\n",
    "result = pd.concat([df_test['PassengerId'], Survived], axis=1)\n",
    "result.to_csv('./../data/result5_1.csv', index=False)"
   ],
   "id": "19444f3130d8766f",
   "outputs": [],
   "execution_count": 58
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "0.78947",
   "id": "da42bf306b218dd9"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T02:02:24.000970Z",
     "start_time": "2025-04-09T02:02:23.941494Z"
    }
   },
   "cell_type": "code",
   "source": [
    "Survived = pd.DataFrame(vote_soft_clf.predict(X_test_new), columns=['Survived'])\n",
    "result = pd.concat([df_test['PassengerId'], Survived], axis=1)\n",
    "result.to_csv('./../data/result5_2.csv', index=False)"
   ],
   "id": "1dff9e20da0c4f66",
   "outputs": [],
   "execution_count": 57
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "0.78229",
   "id": "1c7aba761c01d3ce"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "### 堆叠",
   "id": "79e36fc675afa060"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T02:01:35.233562Z",
     "start_time": "2025-04-09T02:01:35.229577Z"
    }
   },
   "cell_type": "code",
   "source": "from sklearn.ensemble import StackingClassifier",
   "id": "cc3c6f3786f31855",
   "outputs": [],
   "execution_count": 52
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T02:02:06.818629Z",
     "start_time": "2025-04-09T02:02:05.321272Z"
    }
   },
   "cell_type": "code",
   "source": [
    "stack_clf = StackingClassifier(estimators=estimators, cv=5, n_jobs=-1)\n",
    "stack_clf.fit(X_train_new, y_train)"
   ],
   "id": "293d0530b83da93a",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "StackingClassifier(cv=5,\n",
       "                   estimators=[('DecisionTree',\n",
       "                                DecisionTreeClassifier(max_depth=7,\n",
       "                                                       min_samples_leaf=12,\n",
       "                                                       random_state=42)),\n",
       "                               ('RandomForest',\n",
       "                                RandomForestClassifier(max_depth=8,\n",
       "                                                       min_samples_leaf=2,\n",
       "                                                       n_estimators=55,\n",
       "                                                       n_jobs=-1,\n",
       "                                                       random_state=42)),\n",
       "                               ('AdaBoost',\n",
       "                                AdaBoostClassifier(estimator=DecisionTreeClassifier(max_depth=3,\n",
       "                                                                                    min_samples_leaf=13),\n",
       "                                                   n_estimators=90,\n",
       "                                                   random_state=42)),\n",
       "                               ('GradientBoosting',\n",
       "                                GradientBoostingClassifier(max_depth=4,\n",
       "                                                           min_samples_leaf=5,\n",
       "                                                           n_estimators=110,\n",
       "                                                           random_state=42))],\n",
       "                   n_jobs=-1)"
      ],
      "text/html": [
       "<style>#sk-container-id-3 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: #000;\n",
       "  --sklearn-color-text-muted: #666;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-3 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-3 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-3 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: flex;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "  align-items: start;\n",
       "  justify-content: space-between;\n",
       "  gap: 0.5em;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 label.sk-toggleable__label .caption {\n",
       "  font-size: 0.6rem;\n",
       "  font-weight: lighter;\n",
       "  color: var(--sklearn-color-text-muted);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-3 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-3 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-3 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-3 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-3 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 0.5em;\n",
       "  text-align: center;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-3 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>StackingClassifier(cv=5,\n",
       "                   estimators=[(&#x27;DecisionTree&#x27;,\n",
       "                                DecisionTreeClassifier(max_depth=7,\n",
       "                                                       min_samples_leaf=12,\n",
       "                                                       random_state=42)),\n",
       "                               (&#x27;RandomForest&#x27;,\n",
       "                                RandomForestClassifier(max_depth=8,\n",
       "                                                       min_samples_leaf=2,\n",
       "                                                       n_estimators=55,\n",
       "                                                       n_jobs=-1,\n",
       "                                                       random_state=42)),\n",
       "                               (&#x27;AdaBoost&#x27;,\n",
       "                                AdaBoostClassifier(estimator=DecisionTreeClassifier(max_depth=3,\n",
       "                                                                                    min_samples_leaf=13),\n",
       "                                                   n_estimators=90,\n",
       "                                                   random_state=42)),\n",
       "                               (&#x27;GradientBoosting&#x27;,\n",
       "                                GradientBoostingClassifier(max_depth=4,\n",
       "                                                           min_samples_leaf=5,\n",
       "                                                           n_estimators=110,\n",
       "                                                           random_state=42))],\n",
       "                   n_jobs=-1)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-13\" type=\"checkbox\" ><label for=\"sk-estimator-id-13\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>StackingClassifier</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.ensemble.StackingClassifier.html\">?<span>Documentation for StackingClassifier</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></div></label><div class=\"sk-toggleable__content fitted\"><pre>StackingClassifier(cv=5,\n",
       "                   estimators=[(&#x27;DecisionTree&#x27;,\n",
       "                                DecisionTreeClassifier(max_depth=7,\n",
       "                                                       min_samples_leaf=12,\n",
       "                                                       random_state=42)),\n",
       "                               (&#x27;RandomForest&#x27;,\n",
       "                                RandomForestClassifier(max_depth=8,\n",
       "                                                       min_samples_leaf=2,\n",
       "                                                       n_estimators=55,\n",
       "                                                       n_jobs=-1,\n",
       "                                                       random_state=42)),\n",
       "                               (&#x27;AdaBoost&#x27;,\n",
       "                                AdaBoostClassifier(estimator=DecisionTreeClassifier(max_depth=3,\n",
       "                                                                                    min_samples_leaf=13),\n",
       "                                                   n_estimators=90,\n",
       "                                                   random_state=42)),\n",
       "                               (&#x27;GradientBoosting&#x27;,\n",
       "                                GradientBoostingClassifier(max_depth=4,\n",
       "                                                           min_samples_leaf=5,\n",
       "                                                           n_estimators=110,\n",
       "                                                           random_state=42))],\n",
       "                   n_jobs=-1)</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><label>DecisionTree</label></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-14\" type=\"checkbox\" ><label for=\"sk-estimator-id-14\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>DecisionTreeClassifier</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.tree.DecisionTreeClassifier.html\">?<span>Documentation for DecisionTreeClassifier</span></a></div></label><div class=\"sk-toggleable__content fitted\"><pre>DecisionTreeClassifier(max_depth=7, min_samples_leaf=12, random_state=42)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><label>RandomForest</label></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-15\" type=\"checkbox\" ><label for=\"sk-estimator-id-15\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>RandomForestClassifier</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.ensemble.RandomForestClassifier.html\">?<span>Documentation for RandomForestClassifier</span></a></div></label><div class=\"sk-toggleable__content fitted\"><pre>RandomForestClassifier(max_depth=8, min_samples_leaf=2, n_estimators=55,\n",
       "                       n_jobs=-1, random_state=42)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><label>AdaBoost</label></div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-16\" type=\"checkbox\" ><label for=\"sk-estimator-id-16\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>estimator: DecisionTreeClassifier</div></div></label><div class=\"sk-toggleable__content fitted\"><pre>DecisionTreeClassifier(max_depth=3, min_samples_leaf=13)</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-17\" type=\"checkbox\" ><label for=\"sk-estimator-id-17\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>DecisionTreeClassifier</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.tree.DecisionTreeClassifier.html\">?<span>Documentation for DecisionTreeClassifier</span></a></div></label><div class=\"sk-toggleable__content fitted\"><pre>DecisionTreeClassifier(max_depth=3, min_samples_leaf=13)</pre></div> </div></div></div></div></div></div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><label>GradientBoosting</label></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-18\" type=\"checkbox\" ><label for=\"sk-estimator-id-18\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>GradientBoostingClassifier</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.ensemble.GradientBoostingClassifier.html\">?<span>Documentation for GradientBoostingClassifier</span></a></div></label><div class=\"sk-toggleable__content fitted\"><pre>GradientBoostingClassifier(max_depth=4, min_samples_leaf=5, n_estimators=110,\n",
       "                           random_state=42)</pre></div> </div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><label>final_estimator</label></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-19\" type=\"checkbox\" ><label for=\"sk-estimator-id-19\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>LogisticRegression</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.linear_model.LogisticRegression.html\">?<span>Documentation for LogisticRegression</span></a></div></label><div class=\"sk-toggleable__content fitted\"><pre>LogisticRegression()</pre></div> </div></div></div></div></div></div></div></div></div></div></div>"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 53
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T02:02:16.321011Z",
     "start_time": "2025-04-09T02:02:09.967242Z"
    }
   },
   "cell_type": "code",
   "source": [
    "scores = cross_val_score(stack_clf, X_train_new, y_train, cv=5, scoring='accuracy')\n",
    "np.mean(scores)"
   ],
   "id": "80178c41a52a37a0",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(0.8417676228736426)"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 54
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T02:02:17.912129Z",
     "start_time": "2025-04-09T02:02:17.850165Z"
    }
   },
   "cell_type": "code",
   "source": "stack_clf.score(X_train_new, y_train)",
   "id": "8eec7a7e65cb89fa",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9158249158249159"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 55
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T02:02:21.132746Z",
     "start_time": "2025-04-09T02:02:21.082492Z"
    }
   },
   "cell_type": "code",
   "source": [
    "Survived = pd.DataFrame(stack_clf.predict(X_test_new), columns=['Survived'])\n",
    "result = pd.concat([df_test['PassengerId'], Survived], axis=1)\n",
    "result.to_csv('./../data/result6.csv', index=False)"
   ],
   "id": "3278e007f6ac7876",
   "outputs": [],
   "execution_count": 56
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "0.78947",
   "id": "546163d24f62fce6"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "## 五、学习总结",
   "id": "43ef96f5d139e76c"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "本次使用全数据进行预处理，并将分类数据进行 One-Hot 编码。\n",
    "\n",
    "进行了卡方检验，找出了权重前十的特征进行训练。\n",
    "\n",
    "利用 GridSearchCV 网格搜索选出分数最高的最佳参数，训练提交。"
   ],
   "id": "2d9784e17beea176"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "共建立了 7 个模型，分别是：\n",
    "\n",
    "1. LogisticRegression : 逻辑回归\n",
    "2. DecisionTreeClassifier : 决策树\n",
    "3. RandomForestClassifier : 随机森林\n",
    "4. AdaBoostClassifier : 参数权重\n",
    "5. GradientBoostingClassifier : 梯度提升\n",
    "6. VotingClassifier : 投票\n",
    "7. StackingClassifier : 堆叠\n",
    "\n",
    "目前来看 **随机森林** 的效果是最好的，分数从 **0.76315 --> 0.79186** ，排名从只用逻辑回归的 **12980 --> 1231**\n",
    "\n",
    "***排名的上升也是我没有想到的，仅仅提升 2.87% ，上升了 11749 名，这可能也代表了我正式入门了机器学习！***"
   ],
   "id": "5be3e9813f96ffd"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "但仍旧有一些问题：\n",
    "\n",
    "- Boosting、Voting、Stacking 的效益竟然没有 决策树 和 随机森林 高，且使用 Boosting 时有十分严重的过拟合问题，按道理它能够有效防止过拟合的。\n",
    "- 根据两天的不断尝试，调整了各种参数，也怀疑了各种参数，但最终都没有将 score 提升到 0.80 以上（可能是数据预处理需要更加完善）。\n",
    "- 随机森林 使用特征选择后的数据比特征选择前更好，但理论上讲 随机森林 应该可以随机特征选择的。"
   ],
   "id": "b35503d65fe1ec9"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "想法：\n",
    "\n",
    "1. Cabin 特征即使空缺较多也是可以使用的\n",
    "2. 是否独自乘船？也可以作为特征之一\n",
    "3. 决策树 和 随机森林 可能需要增加剪枝\n",
    "4. 需要增加更多种的模型，以提供更多因素供 集成算法 的提升"
   ],
   "id": "e6c35c2b86b95626"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "***总结来看，这些模型能够熟练掌握，但数据处理和模型实际运用上仍需提高！***\n",
    "\n",
    "***虽然说了这么多不足，但实际上这次相对于第一次提升很大了，也算是又上升一个台阶了。***\n",
    "\n",
    "**继续加油！( •̀ ω •́ )✧**"
   ],
   "id": "98b98f860d407013"
  }
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